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import NvRules
def get_identifier():
return "KernelInfo"
def get_name():
return "Kernel Information"
def get_description():
return "Basic kernel information. This independent rule does not map to any section."
# The Evaluate function is used to specify to the rule system this rule's dependencies,
# e.g. the metrics that must have been collected in order for this rule to work properly.
# For rules that are tied to sections, this is guaranteed by the section itself
def evaluate(handle):
# specify which metrics are required
NvRules.require_metrics(handle, ["launch__grid_size", "launch__block_size"])
def apply(handle):
ctx = NvRules.get_context(handle)
# select the default action (kernel)
action = ctx.range_by_idx(0).action_by_idx(0)
# it is now safe to retrieve those metrics, as we declared the dependency in Evaluate
grid_size = int(action.metric_by_name("launch__grid_size").as_double())
block_size = int(action.metric_by_name("launch__block_size").as_double())
# show a message in the user interface
ctx.frontend().message("Kernel " + action.name() + " launch config: " + str(grid_size) + "x" + str(block_size))
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